Acceptance testing An introduction Alessandro Marchetto Fondazione Bruno

Acceptance testing An introduction Alessandro Marchetto Fondazione Bruno Kessler - IRST

Outline • • Introduction Acceptance and Unit testing Table-based testing and Fit/Fitnesse: An Example

Testing • One of the practical methods commonly used to detect the presence of errors (failures) in a computer program is to test it for a set of inputs. I 1, I 2, I 3, …, In, … Our program “Inputs” The output is correct? Expected results =? Obtained results

Test last The most conventional approach… Understand New functionality Implement functionality Write tests Run all tests Rework fail Result? pass Next functionality

Test first “Extreme programming” (XP) champions the use of tests as a development tool … Understand New functionality Add a single test Add code for the test Run all test Rework fail Result? Next functionality Yes pass No Functionality complete?

Test-first with Junit Add a testcase Add the skeleton of the class and methods (without body) Run test Rework Refactoring “improving the structure” Run test

Test first advantages • Each method has associated a test-case • the confidence of our code increases … • It simplifies: • • refactoring restructuring maintenance the introduction of new functionalities • Test first helps in writing the documentation • test cases are good “use samples”

Test levels • Unit testing – this is basically testing of a single function, procedure, class. • Integration testing – this checks that units tested in isolation work properly when put togheter. • System testing – here the emphasis is to ensure that the whole system can cope with real data, monitor system performance, test the system’s error handling and recovery routines. • Acceptance testing – this check that the overall system is functioning as required

Unit Testing • Unit Tests are tests written by the developers to test functionality as they write it. • Each unit test typically tests only a single class, or a small cluster of classes. • Unit tests are typically written using a unit testing framework, such as JUnit (automatic unit tests). • Target errors not found by Unit testing: - Requirements are mis-interpreted by developer. - Modules do not integrate with each other

The tools picture FIT/Fitnesse (High level) Cactus Jemmy/Abbot/JFCUnit/… GUI Business Logic Perfomance and Load Testing JMeter/JUnit. Perf Http. Unit/Canoo/Selenium Junit (Low level) Web UI Persistence Layer Junit/SQLUnit/XMLUnit Cactus is an extension to JUnit that allows for the testing of serverside Java code without having to run a server external to the testing setup

Outline • • Introduction Acceptance and Unit testing Table-based testing and Fit/Fitnesse: An Example

Acceptance Testing • Acceptance Tests are specified by the customer and analyst to test that the overall system is functioning as required (Do developers build the right system? ). • Acceptance tests typically test the entire system, or some large chunk of it. • When all the acceptance tests pass for a given user story (or use case, or textual requirement), that story is considered complete. • An acceptance test could consist of a script of user interface actions and expected results that a human can run. • Ideally acceptance tests should be automated, either using the unit testing framework, or a separate acceptance testing framework.

Acceptance vs. Unit Testing In summary: Acceptance Tests Unit Tests Written by Customer and Analyst. Written by developers. Written using an acceptance testing framework (also unit testing framework). Written using a unit testing framework. (extreme programming) When acceptance tests pass, stop coding. The job is done. (extreme programming) When unit tests pass, write another test that fails. The motivation of acceptance testing is demonstrating working functionalities. The motivation of unit testing is finding faults. Used to verify that the implementation is complete and correct. Used for Integration, System, and regression testing. Used to indicate the progress in the development phase. (Usually as %). Used as a contract. Used for documentation (high level) Used to find faults in individual modules or units (individual programs, functions, procedures, web pages, menus, classes, …) of source code. Used for documentation (low level) Written before the development and executed after. Written and executed during the development. Starting point: User stories, User needs, Use Cases, Textual Requirements, … (the whole system) Starting point: new capability (to add a new module/function or class/method). …. (the unit)

Traditional approaches to acceptance testing • Manual Acceptance testing. User exercises the system manually using his creativity. • Acceptance testing with “GUI Test Drivers” (at the GUI level). These tools help the developer to do functional/acceptance testing through a user interface such as a native GUI or web interface. “Capture and Replay” Tools capture events (e. g. mouse, keyboard) in modifiable script. Disadvantages: expensive, error prone, not repeatable, … Disavantages: Tests are brittle, i. e. , have to be re-captured if the GUI changes.

Outline • • Introduction Acceptance and Unit testing Table-based testing and Fit/Fitnesse: An Example

Table-based approach for acceptance Testing • Starting from a user story (or use case or textual requirement), the customer enters in a table (spreadsheet application, html, Word, …) the expectations of the program’s behavior. • At this point tables can be used as oracle. The customer can manually insert inputs in the System and compare outputs with expected results. inputs Pro: help to clarify requirements, used in System testing, … Cons: expensive, error prone, … output

What is Fit? • The Framework for Integrated Test (Fit) is the most well-known implementation (open source framework) of the table-based acceptance testing approach. • Fit lets customers and analysts write “executable” acceptance tests by means of tables written using simple HTML. • Developers write “fixtures” to link the test cases with the actual system itself. • Fit compares these test cases, written using HTML tables, with actual values, returned by the system, and highlights the results with colors and annotations.

Output Table The picture o ≠ o’ Developer Fixture Test Runner o’ i Customer/ Analyst (i, o) System User Story Fit Table O = expected output O’ = actual output

Fixture Fit provides a set of fixtures: • Column fixture for testing calculations. • Action fixture for testing the user interfaces or workflow. • Row fixture for validating a collection of domain objects. Used to check the result of a query. • Summary fixture to display a summary of all test on a page. • Html fixture to examine and navigate HTML pages. • Table fixture, Command line fixture, …

What is Fit. Nesse? A collaborative testing and documentation tool: • It supports Java (eclipse plug-in), . Net, C++ • It combines Fit with a Wiki Web for writing “natural language requirements” + Fit tables. • It provides a simple way to run tests (Fit tables) and suits. • It Supports Wiki and sub Wikis for managing multiple projects.

How to use Fit. Nesse? • Install and start. • Define the project on the Fit. Nesse Wiki. • Write requirements and fit tables on the Fit. Nesse Wiki. • Write the glue code (fixture), the unit tests and the business logic in your favorite IDE (eclipse). • Execute the acceptance tests by a click on the Web page (test button). • See the results (green or red) of executing the tests on the Web page. “expected 170, actual 190”

Outline • • Introduction Acceptance and Unit testing Table-based testing and Fit/Fitnesse: An Example

An example: the Football-team Application • • • A sports magazine decides to add a new feature to its Website that will allow users to view top football teams according to their ratings. An analyst and a developer get together to discuss the change requirements. The outcome of the discussion is: – a user story card that summarizes the change requirements – a set of acceptance tests – an excel file with sample data

user story (change requirement) set of acceptance tests excel file with sample data

The domain object representing a football team package sport. business. Objects; public class Team { public String name; public int played; public int won; public int drawn; public int lost; public int rating; public Team(String name, int ply, int won, int drawn, int lst) { super(); this. name = name; this. played = played; this. won = won; this. drawn = drawn; this. lost = lost; calculate. Rating(); } private void calculate. Rating() { float value = ((10000 f*(won*3+drawn))/(3*played))/100; rating = Math. round(value); } }

Test 1: Fit Table “verify the rating is calculated properly” • • • For a team, given the number of matches played, won, drawn, and lost, we need to verify that the ratings are calculated properly. The first step is to express the logic using a Fit table. The table created using Excel can be easily converted into a Fit table by just adding a fixture name and modifying the labels. The Fit table on the right represents the first acceptance test case to verify the rating calculation. Now that we have created the Fit table, we need to write the glue code that will bridge the test case to the system under test. “column fixture”

Test 1: Fixture “verify the rating is calculated properly” • • • For each input attribute represented by Columns 1 through 5 in the second row of the Fit table, there is a public member with the same name A public method public long rating() corresponds to the calculation in the sixth column. The rating() method in Verify. Rating creates a Team object using the input data specified by the test case and returns the rating from the Team object; this is where the bridging between the test case and the system under test happens. public class Verify. Rating extends Column. Fixture { public public String team. Name; int played; int won; int drawn; int lost; public long rating() { Team team = new Team(team. Name, played, won, drawn, lost); return team. rating; } }

Test 1: Running “verify the rating is calculated properly” • 1. 2. 3. 4. Here is what happens when you run the test: Fit parses the table and creates an instance of “sample. Verify. Rating” For each row in the table Fit set the values specified in Columns 1 through 5 to the corresponding fields in the fixture. The rating() method is executed to get the actual value to be compared against the expected value specified in the sixth column. If the expected value matches the actual value, then the test passes; otherwise it fails. Launch the test runner … sport. fixtures. Verify. Rating team name played won drawn lost rating() Arsenal 38 31 2 5 83 Aston Villa 38 20 2 16 54 Chelsea 38 35 1 2 93 Dummy 38 35 1 2 100 expected ---------93 actual Wigan 38 26 7 5 75 passed failed exception